Overview • Contents • Screenshots • Resource Filess • API and Functionality • Contributions • License
Welcome to the computer-vision-toolkit repository! This repository is a comprehensive guide for beginners entering the world of computer vision. Here, you'll find a range of Python scripts using OpenCV that cover fundamental topics in computer vision. The scripts are well-commented and user-friendly, guiding you through each step.
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Mono and Stereo Calibration
- Calibration using chessboard and charuco patterns.
- Detailed guidance for mono and stereo calibration processes.
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Distortion Removal
- Scripts for removing lens distortion from images.
- Techniques to improve image quality for further processing.
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Parameter Determination
- Calculating parameters like baseline, field of view (FOV), and focal length.
- Step-by-step instructions to understand and implement these calculations.
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Image Rectification in Stereo Systems
- Procedures for rectifying images from stereo camera systems.
- Methods to align a pair of stereo images for depth perception.
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Disparity and Depth Maps Generation
- Generating disparity maps to estimate depth information.
- Creating depth maps from stereo images.
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Distance Measurement from Images
- Techniques for measuring object distances using previously generated maps.
- Practical examples to understand real-world applications.
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Point Cloud Generation and 3D Visualization
- Scripts to generate point clouds from stereo images.
- Tools for visualizing these points in 3D space.
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Optical Flow from Video Files
- Implementing optical flow algorithms on video files.
- Understanding the motion of objects between frames.
The repository includes a set of example tasks with associated resource files. These are designed to help you practice and refine your skills in computer vision and image processing.
CVToolkit also comes with an extensive API, packed with functionalities for computing various parameters essential for the tasks mentioned above. The API is designed to be intuitive and easy to use, facilitating a smoother learning curve. To begin, clone the repository and navigate to the topic of your interest. Each script is self-contained and includes instructions for setup and execution.
Contributions to CVToolkit are welcome! If you have suggestions, improvements, or new examples, please feel free to submit a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.
© 2023 Mateusz Płonka (SmartMatt). All rights reserved.
